Prioritization of Passive Parameters from Modified Averaging Approach-Based Computation (MAAC) Methodology for Ascertaining Formation of Single and Multi-Location Unintentional Islands

Kulkarni, Nitin; Khedkar, Mohan; Bhende, Chandrashekhar N.; Singh, Sunil K.

doi:10.3390/en15176441

Cited by 1 publication

(1 citation statement)

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“…Passive IDMs measure different electric variables at the PCC such as voltage, current, frequency, phase angle, total harmonic distortion (THD), active power, reactive power, and others [33], without introducing any perturbation. These IDMs operate under the assumption that when an island forms, there will be an imbalance between demand and generation that affects the sensed variables.…”

Section: Literature Review Of Islanding Detection Methodsmentioning

confidence: 99%

Bayesian Entropy Methodology: A Novel Approach to Setting Anti-Islanding Protections with Enhanced Stability and Sensibility

Seguin Batadi,

Martínez,

Molina

2024

Energies

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The risk of unintentional islanding creation in distributed energy systems poses a significant security concern since unintentional islanding formation could lead to a supply of energy outside of the optimal quality limits. This constitutes a risk for users, maintenance personnel, infrastructure, and devices. To mitigate this problem, anti-islanding protections are widely used to prevent the distributed generator from feeding a portion of the radial distribution grid when a protection device trips upstream. However, the effectiveness of these protections heavily relies on properly tuning protection setting thresholds (such as time delay and pickup). This work proposes a novel approach that utilizes entropy as a model and metric of the uncertainty associated with a particular protection setting. By minimizing entropy, the proposed method aims to improve stability and sensitivity, consequently improving the overall performance of anti-islanding protection. Simulation results demonstrate that the Bayesian entropy methodology (BEM) approach achieves enhanced stability in various scenarios, including frequency transients, and demonstrates a notable reduction in the size of the dataset and computational burden, ranging between 91% and 98%, when compared to related works, with an improvement of the uncertainty achieved. The findings of this study contribute to the development of more robust and reliable anti-islanding protections.

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Section: Literature Review Of Islanding Detection Methodsmentioning

confidence: 99%